How much knowledge will be lost to AI? Large language models (LLMs) such as ChatGPT, Google Gemini and Anthropic’s Claude excel at locating, synthesizing and connecting knowledge. They don’t add to the stock of knowledge.
By contrast, when humans answer questions, such as whether Einstein should be energy secretary, they often pursue novel avenues of inquiry, creating new knowledge and insight as they go. They do this for a variety of reasons: salary, wealth, fame, tenure, “likes,” clicks, curiosity.
If LLMs come to dominate the business of answering questions, those incentives shrivel. There is little reward to creating knowledge that then gets puréed in a large language blender.
Consider the fate of Stack Overflow, a website where software developers ask and answer questions, becoming both a wellspring and repository for knowledge.
But then developers started putting their questions to ChatGPT. Six months after its introduction in November 2022, the number of questions on Stack Overflow had fallen 25%
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